iPhone 17 Pro
Geekbench AI Score
5155
Single Precision Score
38508
Half Precision Score
52295
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Pijiuhua |
| Upload Date | April 15 2026 03:10 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A19 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.5 |
| Model | iPhone 17 Pro |
| Model ID | iPhone18,1 |
| Motherboard | V53AP |
| CPU Information | |
|---|---|
| Name | Apple A19 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.26 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 11.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2385
443.4 IPS |
|
|
Image Classification (HP)
|
100% |
15780
2.93 KIPS |
|
|
Image Classification (Q)
|
97% |
22538
4.21 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2182
35.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
20078
325.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
24985
405.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7994
9.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
147628
172.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
276935
324.6 IPS |
|
|
Object Detection (SP)
|
100% |
2577
204.4 IPS |
|
|
Object Detection (HP)
|
100% |
18260
1.45 KIPS |
|
|
Object Detection (Q)
|
89% |
25551
2.05 KIPS |
|
|
Face Detection (SP)
|
100% |
4621
54.9 IPS |
|
|
Face Detection (HP)
|
100% |
42248
502.0 IPS |
|
|
Face Detection (Q)
|
100% |
56727
674.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7729
59.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
103971
801.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
169367
1.32 KIPS |
|
|
Style Transfer (SP)
|
100% |
21067
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
256876
330.2 IPS |
|
|
Style Transfer (Q)
|
96% |
323978
418.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4999
184.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
57388
2.12 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85359
3.15 KIPS |
|
|
Text Classification (SP)
|
99% |
6649
8.87 KIPS |
|
|
Text Classification (HP)
|
99% |
11598
15.5 KIPS |
|
|
Text Classification (Q)
|
92% |
11693
15.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
4950
85.3 IPS |
|
|
Machine Translation (HP)
|
100% |
11180
192.6 IPS |
|
|
Machine Translation (Q)
|
98% |
12358
213.6 IPS |
